Enabling Uniform Computer Interaction Experience for Blind Users through Large Language Models.

Satwik Ram Kodandaram, Utku Uckun, Xiaojun Bi, I V Ramakrishnan, Vikas Ashok
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Abstract

Blind individuals, who by necessity depend on screen readers to interact with computers, face considerable challenges in navigating the diverse and complex graphical user interfaces of different computer applications. The heterogeneity of various application interfaces often requires blind users to remember different keyboard combinations and navigation methods to use each application effectively. To alleviate this significant interaction burden imposed by heterogeneous application interfaces, we present Savant, a novel assistive technology powered by large language models (LLMs) that allows blind screen reader users to interact uniformly with any application interface through natural language. Novelly, Savant can automate a series of tedious screen reader actions on the control elements of the application when prompted by a natural language command from the user. These commands can be flexible in the sense that the user is not strictly required to specify the exact names of the control elements in the command. A user study evaluation of Savant with 11 blind participants demonstrated significant improvements in interaction efficiency and usability compared to current practices.

通过大型语言模型实现盲人用户统一的计算机交互体验。
盲人必须依靠屏幕阅读器与计算机交互,他们在浏览不同计算机应用程序的多样化和复杂的图形用户界面时面临相当大的挑战。各种应用程序接口的异构性通常要求盲人用户记住不同的键盘组合和导航方法,以便有效地使用每个应用程序。为了减轻异构应用程序接口带来的交互负担,我们提出了Savant,这是一种由大型语言模型(llm)提供支持的新型辅助技术,它允许盲人屏幕阅读器用户通过自然语言与任何应用程序接口进行统一的交互。新颖的是,当用户发出自然语言命令提示时,Savant可以在应用程序的控制元素上自动执行一系列繁琐的屏幕阅读器操作。这些命令可以很灵活,因为用户不需要在命令中严格指定控制元素的确切名称。一项由11名盲人参与的Savant用户研究评估显示,与目前的做法相比,在交互效率和可用性方面有了显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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